Zhang Tianyu, Pabst Breana, Klapper Isaac, Stewart Philip S
Department of Mathematical Sciences, Montana State University, Bozeman, Montana, United States of America.
Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana, United States of America.
PLoS One. 2013 Dec 23;8(12):e83626. doi: 10.1371/journal.pone.0083626. eCollection 2013.
A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.
本文推导了一种用于分析和预测微生物生物膜内基因和蛋白质表达的时空模式的理论。该理论整合了溶质反应与扩散、微生物生长、mRNA或蛋白质合成、生物量平流以及基因转录本或蛋白质周转等现象。案例研究表明了该理论模拟非均匀空间模式以及预测生物膜中微生物活性的能力，这些活性在性质上与浮游细胞的活性不同。分析的具体情形包括一个可诱导的绿色荧光蛋白（GFP）或荧光蛋白报告基因、一个受氧气抑制的反硝化基因、一个酸应激反应基因以及一个群体感应回路。结果表明，可诱导的稳定荧光蛋白或报告不稳定蛋白所揭示的活性模式高估了活性区域。这是由于平流扩散和有限的蛋白质周转速率所致。在因代谢底物限制或代谢产物积累而诱导的基因的情况下，预测最大表达出现在生物膜的内部层。一个包含氧气响应负调控因子的群体感应系统表现出与分批浮游培养的任何阶段都不同的行为。尽管这里的分析仅限于最多两个底物和两个基因的同时相互作用，但该框架适用于任意大的基因和代谢物网络。将生物膜中的反应 - 扩散建模扩展到单个基因和基因网络的分析是一项重要进展，它与不断发展的分子和遗传实验技术工具相契合。
